Search Results (248)

This study extends our prior blockchain-based traceability framework, WEave, for application to a furniture supply chain scenario, while using the original multi-tier apparel supply chain as an anchoring use case. We integrate circular economy principles such as product reuse, recycling traceability, and full lifecycle transparency to bolster sustainability and resilience in supply chains by enabling data-driven accountability and tracking for closed-loop resource flows. The enhanced approach can track post-consumer returns, use of recycled materials, and second-life goods, all represented using a closed-loop supply chain topology. We describe the extended network architecture and smart contract logic needed to capture circular lifecycle events, while proposing new metrics for evaluating lifecycle traceability and reuse auditability. To validate the extended framework, we outline simulation experiments that incorporate circular flows and cross-industry scenarios. Results from these simulations indicate improved transparency on recycled content, audit trails for returned products, and acceptable performance overhead when scaling to different product domains. Finally, we offer conclusions and recommendations for implementing WEave functionality into real-world settings consistent with the goals of digital, resilient, and sustainable supply chains. Full article

This paper presents a method to model and optimize the supply chain processes for floating offshore wind turbines using a network model based on Generalized Multi-Commodity Network Flows (GMCNF). The proposed method represents production bases, base ports, installation sites, component transfer areas, and transportation routes as nodes and arcs within the network. The installation process is modeled using three transport concepts: assembling components at the base port, direct assembly and installation at the installation site, and transferring components to the installation vessel at a nearby port. These processes are expressed as a linear network model, with the objective function set to minimize total transportation and assembly costs. The optimal transportation network is derived by solving the network problem while incorporating constraints such as supply, demand, and transportation capacity. Case studies demonstrate the method’s effectiveness in optimizing the supply chain and evaluating potential new production site locations for floating foundations, considering overall supply chain optimization. Full article

With the continuous expansion and increasing operational complexity of high-speed railway networks, there is a growing need for more flexible and efficient EMU (Electric Multiple Unit) routing strategies. To address these challenges, in this paper, we propose a multi-day flexible circulation model that minimizes total connection time and deadheading mileage. A multi-commodity network flow model is formulated, incorporating constraints such as first-level maintenance intervals, storage capacity, train coupling/decoupling operations, and train types, with across-day consistency. To solve this complex model efficiently, a heuristic decomposition algorithm is designed to separate the problem into daily service chain generation and EMU assignment. A real-world case study in the Beijing–Baotou high-speed corridor demonstrates the effectiveness of the proposed approach. Compared to a fixed strategy, the flexible strategy reduces EMU usage by one unit, lowers deadheading mileage by up to 16.4%, and improves maintenance workload balance. These results highlight the practical value of flexible EMU deployment for large-scale, multi-day railway operations. Full article

Increasing the shelf-life of fruits and vegetables using edible natural substances after harvest is economically important and can be useful for human health. Postharvest techniques help maintain the quality of edible tissues resulting in extended marketing periods and reduced food waste. The edible coating on perishable commodities is a common technique used by the food industry during the postharvest supply chain. The objective of this research was to study the effect of edible oil to minimize the loss of postharvest physio-chemical and nutritional attributes of bananas. The study selected two banana cultivars (Musa, ‘Cavendish’ and ‘Milk’) to conduct this experiment, and two edible oils (olive oil (Olea europaea) and moringa oil (Moringa peregrina)) were applied as an edible coating under two different storage conditions (15 and 25 °C). The fruit’s physio-chemical properties including weight loss, firmness, color, total soluble solids (TSS), pH, titratable acidity (TA), TSS: TA ratio, and mineral content were assessed. The experiment lasted for 12 days. The physicochemical properties of the banana coated with olive and moringa oils were more controlled than the non-coated (control) banana under both storage temperatures (15 °C and 25 °C). Coated bananas with olive and moringa oils stored at 15 °C resulted in further inhibition in the ripening process. There was a decrease in weight loss, retained color, and firmness, and the changes in chemical parameters were slower in banana fruits during storage in the olive and moringa oil-coated bananas. Minerals were highly retained in coated Cavendish bananas. Overall, the coated samples visually maintained acceptable quality until the final day of storage. Our results indicated that olive and moringa oils in this study have the potential to extend the shelf-life and improve the physico-chemical quality of banana fruits. Full article

Considering consumers’ low-carbon preferences, this article analyzes a manufacturer’s price and carbon abatement strategies, as well as a retailer’s price and promotion strategies, in a centralized game, where the manufacturer and the retailer jointly make decisions, and a decentralized game, where the two parties each make decisions simultaneously. This study discusses the impact of the carbon abatement cost coefficient, promotion cost coefficient, sensitivity coefficient of consumer demand to carbon abatement rate or promotion rate, or carbon tax rate on the manufacturer’s carbon abatement rate, commodity’s retail price, and retailer’s promotion rate. This article also discusses the impact of any one of the main parameters on supply chain profit. Through comparisons of the above two games, this article concludes that the former is better than the latter for firms, consumers, and the environment. This article also concludes that a reduction in the carbon abatement cost coefficient, a rise in the sensitivity coefficient of consumer demand to the carbon abatement rate, or a rise in the carbon tax rate increases the manufacturer’s optimal carbon abatement rate. A relatively high carbon abatement rate means relatively low CO₂ emissions, which are environmentally friendly and conducive to sustainable development at the ecological level. The foregoing conclusions provide governments with references for making carbon tax policies and also offer firms references for making decisions. Full article

In a dynamic global market, platinum-group metals (PGMs), particularly palladium, are in high demand across various industries due to their unique properties. Palladium plays a crucial role in environmentally friendly technologies, such as catalytic converters, which mitigate harmful automotive emissions. Additionally, it is essential for clean energy production, particularly in hydrogen generation, which makes palladium a critical resource for building a sustainable and secure supply chain. This study evaluates the prospects of the palladium market through strategic analysis, focusing on the Russian mining and metals company PJSC MMC Norilsk Nickel. The research employs strategic and industry analysis methods to examine palladium production, market dynamics, and technological advancements, as well as emerging applications in the context of a green economy. The article analyzes the economics of palladium production, including price volatility driven by stringent environmental regulations and the rising adoption of electric vehicles. The palladium market faces challenges such as a constrained resource base, supply disruptions due to sanctions, price instability, and growing demand from key sectors, particularly the automotive industry. Nevertheless, innovation-driven trends offer promising opportunities for market growth, aligning with sustainable development principles and the transition toward a green, low-carbon economy in both established and emerging markets. As a key scientific contribution, this study proposes a modified methodological approach to industry analysis, enabling the assessment of a mining and metals company’s competitive sustainability in the palladium market over the medium and long term. Furthermore, the research models the life cycle of palladium as a commodity, considering evolving market trends and the rapid development of new industries within the green economy. Full article

Natural gas with a high carbon dioxide (CO₂) content presents significant operational and environmental challenges when used as a fuel. A high CO₂ content lowers the calorific value of natural gas, reducing its fuel efficiency and increasing the risk of corrosion in pipelines and processing equipment. Consequently, such natural gas must be purified to reduce the CO₂ content to acceptable levels before it can be effectively used as a fuel. Various technologies for natural gas purification are currently employed, primarily focusing on CO₂ removal. This research explores an innovative approach where highly contaminated natural gas is utilized to synthesize hydrogen for subsequent methanol production. Methanol synthesis necessitates both hydrogen and CO₂, integrating the use of by-products effectively in the production chain. Following the production of methanol, it is then converted into dimethyl ether (DME), a compound with considerable value as a clean fuel alternative due to its lower emissions when burnt. The open-source COCO simulator was used to model and simulate these processes, allowing for the creation of a detailed process flowsheet. The simulation covered four main stages: (1) purification of the natural gas to remove excess CO₂, (2) production of hydrogen, (3) synthesis of methanol using the hydrogen and captured CO₂, and (4) conversion of methanol to DME. This integrated approach mitigates the issues associated with high CO₂ content in natural gas and leverages this component as a valuable feedstock, demonstrating a comprehensive use of all extracted compounds. The proposed process illustrates a promising route for utilizing highly contaminated natural gas, potentially transforming an environmental liability into valuable chemical commodities. Full article

Digital agriculture has rapidly developed in the last decade in many countries where the share of agricultural production is a significant part of the total volume of gross production. Digital agroecosystems are developed using a variety of IT solutions, software and hardware tools, wired and wireless data transmission technologies, open source code, Open API, etc. A special place in agroecosystems is occupied by electronic payment technologies and blockchain technologies, which allow farmers and other agricultural enterprises to conduct commodity and monetary transactions with suppliers, creditors, and buyers of products. Such ecosystems contribute to the sustainable development of agriculture, agricultural engineering, and management of production and financial operations in the agricultural industry and related industries, as well as in other sectors of the economy of a number of countries. The introduction of crypto solutions in the agricultural sector is designed to create integrated platforms aimed at helping farmers manage supply lines or gain access to financial services. At the same time, there are risks of illegal use of computing power for cryptocurrency mining—cryptojacking. This article offers a thorough risk assessment of cryptojacking attacks on endpoint systems, focusing on identifying critical vulnerabilities within IT infrastructures and outlining practical preventive measures. The analysis examines key attack vectors—including compromised websites, infected applications, and supply chain infiltration—and explores how unauthorized cryptocurrency mining degrades system performance and endangers data security. The research methodology combines an evaluation of current cybersecurity trends, a review of specialized literature, and a controlled experiment simulating cryptojacking attacks. The findings highlight the importance of multi-layered protection mechanisms and ongoing system monitoring to detect malicious activities at an early stage. Full article

Vegetables are commodities frequently sold in local markets and have been associated with foodborne outbreaks in short and local supply outlets worldwide. These outbreaks could potentially be mitigated through the implementation of good handling practices (GHPs) at points of sale. Numerous studies have assessed microbiological contamination in small-scale vegetable outlets in developing countries. In contrast, research on these risks in developed countries is comparatively scarce. However, with the increasing demand for vegetables, along with the increasing popularity of local markets, there is potential for an increase in foodborne outbreaks in developed countries. This study aimed to perform a microbiological assessment in local and short supply chain outlets of farmers in Portugal, as a case study, and to observe behaviors regarding GHPs in these outlets. The study was performed before and after the implementation of improved GHPs. This research employed quantitative analysis to measure the microbial load on vegetables, bench surfaces, and vendors’ hands. Additionally, a qualitative analysis was conducted to understand farmers’ behavior regarding GHPs using observational methods. Microbial hazards were detected in vegetables, on surfaces, and on hands both before and after the implementation of these practices, although the implementation of GHPs reduced the number of contaminations potentially associated with the practices used at the outlets. The results of this study highlight the importance of implementing GHPs in local and short supply chain markets for vegetables and fruits in developed countries, not only to protect consumers’ health, but also the farmers’ businesses. Full article

Concentrated apple juice (AJC) is a globally traded commodity, with major producers such as China, Poland, and the United States supplying AJC to markets worldwide. The aim of this article is to determine the competitive position of the main global exporters of concentrated apple juice. It also seeks to analyze changes in their positions over the period from 2005 to 2023. Assessing competitive position is important for several economic and business reasons, including identifying leading exporters and recognizing both growing and declining markets. The competitive position was measured using Market Share (MS) indicators, Gross and Net Export Orientation indicators (E_gr, E_net), and the Revealed Comparative Advantage (RCA) index. The results reveal significant structural shifts in global AJC trade. Most notably, China’s declining competitiveness, reflected across all indicators, led to its loss of market leadership. This raises questions about the reasons for this decline and whether it presents opportunities for other exporters. This signals a broader reconfiguration in the global AJC supply chain, driven in part by domestic economic changes, such as rising consumption and decreasing export orientation. Simultaneously, other countries, particularly in Eastern Europe, show varying degrees of competitive growth, with Moldova and Ukraine emerging as key players. These trends suggest a diversification of supply sources and a more fragmented competitive landscape. Although national differences persist, the analysis indicates that structural and economic transformations, rather than short-term price signals, are driving the evolving global competitiveness in the AJC market. The observed weak correlations between prior-year apple prices and RCA confirm that broader market and policy factors play a more decisive role. Full article

The fresh produce supply chain sector is a vital pillar of any society and an indispensable part of the national economic structure. As a significant segment of the agricultural market, accurately forecasting vegetable prices holds significant importance. Vegetable market pricing is subject to a myriad of complex influences, resulting in nonlinear patterns that conventional time series methodologies often struggle to decode. Future planning for commodity pricing is achievable by forecasting the future price anticipated by the current circumstances. This paper presents a price forecasting methodology for tomatoes which uses price and production data taken from 2008 to 2021 and analyzed by means of advanced deep learning-based Long Short-Term Memory (LSTM) networks. A comparative analysis of three models based on Root Mean Square Error (RMSE) identifies LSTM as the most accurate model, achieving the lowest RMSE (0.2818), while SARIMA performs relatively well. The proposed deep learning-based method significantly improved the results versus other conventional machine learning and statistical time series analysis methods. Full article

Traditional horticultural information systems lack fine-grained, transparent on-farm event traceability, often providing only high-level post-harvest summaries. These systems also fail to standardise and integrate diverse data sources, ensure data privacy, and scale effectively to meet the demands of modern agriculture. Concurrently, rising requirements for global environmental, social, and governance (ESG) compliance, notably Scope 3 emissions reporting, are driving the need for farm-level visibility. To address these gaps, this study proposes a novel traceability framework tailored to horticulture, leveraging global data standards. The system captures key on-farm events (e.g., irrigation, harvesting, and chemical applications) at varied resolutions, using decentralised identification, secure data-sharing protocols, and farmer-controlled access. Built on a progressive Web application with microservice-enabled cloud infrastructure, the platform integrates dynamic APIs and digital links to connect on-farm operations and external supply chains, resolving farm-level data bottlenecks. Initial testing on Victorian farms demonstrates its scalability potential. Pilot studies further validate its on-farm interoperability and support for sustainability claims through digitally verifiable credentials for an international horticultural export case study. The system also provides a tested baseline for integrating data to and from emerging technologies, such as farm robotics and digital twins, with potential for broader application across agricultural commodities. Full article

Seafood is a valuable commodity with increasing demand, traded for billions of USD each year. The volatility in supply chains and fluctuating prices contribute to the susceptibility of the seafood market to food fraud. Analytical methods are required to identify seafood in processed foods to ensure food authenticity and compliance with European laws. To address this need, we developed and validated a DNA metabarcoding method for the authentication of crustaceans and cephalopods in processed food samples, as both are prone to food fraud, especially in mixed products. A ~200 bp barcode of the mitochondrial 16S rDNA was selected as the marker for identification and sequenced on Illumina platforms. The DNA metabarcoding method utilizes two primer systems, one for the amplification of crustacean DNA and another for cephalopods. The crustacean primer system comprises two forward and two reverse primers, while the cephalopod primer system includes three forward and one reverse primer. DNA extracts from reference materials, model foods, processed foodstuffs, and DNA extract mixtures were investigated. Even species with a close phylogenetic relationship were successfully identified and differentiated in commercial samples, while single species were detected at amounts as low as 0.003% in model foods. However, false-negative results were obtained for certain species in DNA extract mixtures, which are most likely due to degraded or low-quality DNA and can best be prevented by optimized DNA extraction procedures. Our DNA metabarcoding method demonstrates strong potential as a qualitative screening tool in combination with other in-house DNA metabarcoding methods for food authentication in routine analysis. Full article

Food safety is a global issue that can be enhanced by collaboration with reliable suppliers. Given the complexities of international supply chains, identifying reliable suppliers is often challenging and resource-intensive. Integrating artificial intelligence (AI) offers a valuable opportunity to improve efficiency in this process. The aim of the present study was to develop a quantitative supplier assessment scheme for implementation in an AI-supported database. The framework developed incorporates different indicators, including the hazard risk, incident category level, vulnerability of a commodity, audit performance, logistic performance index, gross domestic product (GDP) growth, and GDP per capita. Each indicator is evaluated according to its own distinct assessment. Ultimately, the sub-assessments are integrated into the calculation of a supplier’s overall risk score. Hereby, it is possible to set individual weightings for each indicator. Manual testing using an exemplary selected supplier yielded promising results, indicating that the next steps involve implementation into an AI-supported database. It can be concluded that such an assessment framework can be an effective method for the identification of reliable suppliers. A future challenge will be to establish incentives to make audit data freely available, as these are often restricted and cannot be considered in the supplier risk assessment. Full article

The transition toward sustainable food systems is a critical challenge for the European Union (EU), requiring integrated policies and collaborative action. However, the complexity of food systems and the diverse interests of stakeholders often hinder effective progress. To apply a systemic approach and deliver context-specific solutions, it is necessary to establish key commodity/supply chain groups that include diverse perspectives from multiple stakeholders. Focusing on the Italian wheat supply chain, this research addresses the gap in understanding stakeholder relationships and their influence on the definition and implementation of sustainability measures. It introduces Net-Map analysis as a fit-for-purpose, multistakeholder, participatory approach to map and analyze these relationships, identifying key actors, power dynamics, and opportunities for fostering collaboration. Through a participatory workshop and in-depth interviews, the study gathered data providing insights into stakeholder roles and leverage points. The findings contribute to improved stakeholder involvement in decision-making processes, ultimately supporting the development of a more resilient and sustainable wheat supply chain in Italy. Full article